DALL-E OpenAI Demo

Creating images and pieces of art has become simple and quick, thanks to the incorporation of artificial intelligence into the art industry. Software engineers have created various AI tools and programs that enable professional and aspiring artists to generate high-quality and unique pieces of art.

One of the latest AI art generators is DALL-E 2. This neural network will enable you to generate original images from simple text captions. But how does DALL-E work? Do you need to be a coding expert to use it? What dataset does the DALL-E use? This article will tell you everything you need to know about DALL-E and provide you with a simple DALL-E OpenAI demo for more detail.

What Is DALL-E?

DALL-E is a neural network designed by OpenAI to enable both professional and amateur artists to generate images from text descriptions. This is an artificial intelligence (AI) program that utilizes the 12-billion parameter model of OpenAI’s GPT-3 model. In short, DALL-E is a limited version of the GPT-3 model, meaning that it’s only available to the people who have been on its waitlist, and that a cloud-based DALL-E API is needed to run this AI art generator.  

Fortunately, DALL-E can interpret natural texts like “green gloves,” “red pants,” “a yellow hat,” etc. When you input these texts, DALL-E AI will generate corresponding images, allowing you to translate your thoughts into words. This program creates images of genuine objects as well as those that don’t exist. While many AI art generators created in the 2000s can create realistic images, some of them can’t generate them from text prompts like DALL-E. So, working with DALL-E will be a plus, as it can generate genuine images from natural language prompts.

DALL-E understands natural language prompts and rarely fails to produce the desired images, meaning that you can create unique and valuable pieces of art, even without the prerequisite skills and creativity. You simply have to command your system using text prompts that describe the kind of image you have in mind–you don’t need to be a coding expert to use DALL-E successfully. Apart from generating original images from text, DALL-E also applies the transformation to existing images and credibly combines dissimilar concepts.

Demo of DALL-E Open AI

To create images with the DALL-E AI image generator, you’ll need to train your AI art generator with images and descriptions. Start by encoding the images through an encoder so that they can be turned into tokens–you’ll also need to encode image descriptions using a description encoder. After encoding, feed the outputs through an auto-regressive model decoder to successfully predict the next token. You’ll get the cross-entropy loss that occurs between the model estimation logits and the real image encodings from the image encoder.

If you are using an image caption, you’ll need to encode and feed the special beginning of sequence (BOS) token through the decoder. This token will be tested sequentially, depending on the decoder’s anticipated supply over the subsequent token. The image token sequence is decoded using a simple decoder. Then, you can select your preferred images. Here is a video demo of how DALL-E from OpenAI works.

Finally, please note that DALL-E uses a transfer neural architecture to generate images from text prompts, but the text needs to be modeled into a single stream of data so that it can be understood by the neural architecture. 

Pretty soon, OpenAI will make DALL-E 2 available for use to its waitlist, and you’ll be able to try out a DALL-E demo for yourself. 

Stay tuned for our implementation of DALL-E 2 as soon as it becomes available.